1. Field of the Invention
The present invention relates to an image processing device and method, and in particular to an image processing device and an image processing method that conduct color balance correction with respect to a color image.
2. Description of the Related Art
Among printers that form a color image, subtle differences arise in color tint (gray balance, etc.) of the image due to differences in the machines and variations in environmental conditions, even if the printers are of the same model. The following technologies are known as technologies that correct individual differences in color tint.
(1) Correction Based on Colorimetric Processing
A test chart is created in which numerous patches whose densities or colors are mutually different are disposed, the individual patches of the created test chart are measured with a colorimeter mounted on the printer or are read by a scanner or the like, and parameter for controlling image quality (color tint) is corrected in accordance with the colorimetric values of the individual patches.
(2) Correction Based on Comparison with Color Sample
Color sample for patches is prepared in advance, a user compares the individual patches on the test chart created by the printer with the color sample, the user selects, from among the individual patches on the test chart, the patch thought to be the closest to the sample, and then correction of the parameter is conducted on the basis of the result of the patch selection by the user.
(3) Correction by Appropriately Selecting Plural Types of Parameters Prepared in Advance
Plural types of parameters corresponding to mutually different conditions are prepared in advance, and correction is conducted by selectively using parameters corresponding to condition at the time of image formation. For instance, technology where color conversion parameters are prepared for each environmental condition and the color conversion parameters are switched in accordance with the environmental condition detected by an environment, and technology where plural gamma coefficients are learned in advance by a neural net and the gamma coefficients are switched in accordance with toner characteristics, are known.
However, although the correction of (1) can correct with high precision individual differences of printers, there is the problem that the cost increases because it is necessary to either dispose a colorimeter in the printer or prepare a separate scanner. Also, because the work of comparing the patches with the sample, which requires skill, is left to the user, there are drawbacks in that an enormous burden is placed on the user and correction precision is largely dependent on the skill level of the user in regard to the work of the comparison. There is also the problem that correction precision drops in accompaniment with changes in the sample over time.
With respect to the correction of (3), for example, in a case where the color conversion parameters are switched in accordance with environmental condition, it is necessary to prepare an environmental chamber for exposing the printer to various types of environmental conditions in order to obtain color conversion parameters corresponding to various types of environmental conditions, and there is the problem that this costs much and is troublesome. Also, in a case where plural gamma coefficients are learned in advance by a neural net and the gamma coefficients are switched in accordance with toner characteristics, control for switching the parameters becomes extremely complex.